Demo Data from EDBT 2026 / reviewers in the wild / expert
Liang Schweizer
dblp:68/10258
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 2011
—ORCID · unresolved
Domains — the database's venue-derived domains; a paper can count in several
Applied, interdisciplinary, general and emerging computing · 1
Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.
| Interdisciplinary, comprehensive, and emerging computing
1 paper |
Bioinformatics and computational biology · 77% Medical and health informatics · 23% |
Topics — the 1 heaviest of 2, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Bioinformatics and computational biology › biostatistics
dose-response analysis |
0.1 | 1 | 2011 | SDRS - an algorithm for analyzing large-scale dose-response data · Bioinform. 2011 |
Methods — techniques the papers use, named apart from their topics
sigmoidal curve fitting · 0.1grid search · 0.1
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2011 | SDRS - an algorithm for analyzing large-scale dose-response dataabstractSUMMARY: Dose-response information is critical to understanding drug effects, yet analytical methods for dose-response assays cannot cope with the dimensionality of large-scale screening data such as the microarray profiling data. To overcome this limitation, we developed and implemented the Sigmoidal Dose Response Search (SDRS) algorithm, a grid search-based method designed to handle large-scale dose-response data. This method not only calculates the pharmacological parameters for every assay, but also provides built-in statistic that enables downstream systematic analyses, such as characterizing dose response at the transcriptome level. AVAILABILITY: Bio::SDRS is freely available from CPAN (www.cpan.org). CONTACTS: [email protected]; [email protected] SUPPLEMENTARY INFORMATION: Supplementary data is available at Bioinformatics online. Rui-Ru Ji, Nathan O. Siemers, Liang Schweizer, Robert E. Bruccoleri |
Bioinform. | 4 |